Traffic data simulator
First Claim
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1. A method comprising:
- receiving sensor data representing traffic patterns from one or more sensors;
identifying holiday traffic data from the sensor data, the holiday traffic data associated with multiple repeating time epochs for multiple holidays;
calculating a plurality of clusters for the holiday traffic data, wherein at least one of the plurality of clusters is defined by a variable centroid;
identifying a dominant traffic pattern cluster from the plurality of clusters; and
storing the dominant traffic pattern cluster in a traffic prediction model,wherein a road layout or a traffic signal pattern is tested using simulated traffic data generated from the traffic prediction model and the dominant traffic pattern cluster.
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Abstract
In one embodiment, traffic data that originates from sensors, cameras, or observations is analyzed. The traffic data is associated with multiple repeating time epochs or intervals. The traffic data is divided into clusters using a clustering technique. The traffic data may be collected on specific days such as holidays. The holiday traffic data may be divided data into clusters and a dominant traffic pattern cluster that represents a holiday classification is identified. The dominant traffic pattern cluster is stored in a traffic prediction model.
58 Citations
19 Claims
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1. A method comprising:
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receiving sensor data representing traffic patterns from one or more sensors; identifying holiday traffic data from the sensor data, the holiday traffic data associated with multiple repeating time epochs for multiple holidays; calculating a plurality of clusters for the holiday traffic data, wherein at least one of the plurality of clusters is defined by a variable centroid; identifying a dominant traffic pattern cluster from the plurality of clusters; and storing the dominant traffic pattern cluster in a traffic prediction model, wherein a road layout or a traffic signal pattern is tested using simulated traffic data generated from the traffic prediction model and the dominant traffic pattern cluster. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An apparatus comprising:
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at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, receiving holiday traffic data from one or more sensors; dividing the holiday traffic data into clusters; identifying a first dominant traffic pattern cluster corresponding to major holidays; identifying a second dominant traffic pattern cluster corresponding to minor holidays; receiving a request for traffic that indicates a holiday date; and accessing either the first dominant traffic pattern cluster or the second dominant traffic pattern cluster depending on whether the holiday data in a major holiday or a minor holiday, wherein a road layout or a traffic signal pattern is tested using simulated traffic data generated from the first dominant traffic pattern cluster or the second dominant traffic pattern cluster. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A non-transitory computer readable medium including instructions that when executed are operable to:
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receive sensor data from one or more sensors; identify holiday traffic data measured in the sensor data, wherein the holiday traffic data is organized into time intervals; divide the measured holiday traffic data within the time intervals into data clusters, wherein the data clusters are variably defined using a clustering technique according to a list of holiday classifications; calculate statistical parameters of the measured traffic data within the time intervals, wherein simulated traffic data is generated based on the statistical parameters, receive a request for a traffic prediction including a holiday classification; and access the data clusters based on the holiday classification, wherein a road layout or a traffic signal pattern is tested using the simulated traffic data.
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Specification